• ISSN: 2010-0248 (Print)
    • Abbreviated Title: Int. J. Innov.  Manag. Technol.
    • Frequency: Quarterly
    • DOI: 10.18178/IJIMT
    • Editor-in-Chief: Prof. Jin Wang
    • Managing Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Google Scholar, CNKI, Ulrich's Periodicals Directory,  Crossref, Electronic Journals Library.
    • E-mail: ijimt@ejournal.net
HOME > Archive > 2012 > Volume 3 Number 3 (Jun. 2012) >
IJIMT 2012 Vol.3(3): 250-254 ISSN: 2010-0248
DOI: 10.7763/IJIMT.2012.V3.232

Adaptive Neurofuzzy Inference System in the Application of the Financial Crisis Forecast

Hui Fang

Abstract—The financial crisis must be faced in the competitive financial market risks, the root causes of the improper handling of the financial leverage of the banks. Therefore, how to control financial risk is one of the Bank is committed to academic. At present, all financial institutions to use more traditional financial analysis as well as external ratings to measure its risk, but this method is easy because of the subjective will of the individual risk assessment of the status of the bias. This study is the use of Adaptive Network- Based Fuzzy Inference System(ANFIS) prediction of the crisis of corporate finance.

In this study, factor analysis of the screening variables, the use of ANFIS as a research method, based Artificial Neural Networks, and Artificial Neural Networks (ANN), compared to view the features and accuracy of both the pros and cons. The results showed that: ANN accuracy rate of 89.49% on ANFIS correct rate of 93.94% on ANFIS correct rate was significantly higher than that of ANN, said the feasibility and effectiveness of the ANFIS prediction of corporate financial crisis is good compared to ANN.

Index Terms—Adaptive neuro fuzzy inference system, neural networks, the financial crisis.

The author is with the School of Computer, Wuhan University, Hubei China (e-mail: fanghui@whu.edu.cn)

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Cite: Hui Fang,"Adaptive Neurofuzzy Inference System in the Application of the Financial Crisis Forecast," International Journal of Innovation, Management and Technology vol. 3, no. 3, pp. 250-254, 2012.

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